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Results: 1 to 20 of 112

1.

Challenges in prognostic analysis.

Concato J.

Cancer. 2001 Apr 15;91(8 Suppl):1607-14. Review. No abstract available.

PMID:
11309759
[PubMed - indexed for MEDLINE]
2.
3.

Clinical problems, computational solutions: a vision for a collaborative future.

Levine RF.

Cancer. 2001 Apr 15;91(8 Suppl):1595-602. No abstract available.

PMID:
11309757
[PubMed - indexed for MEDLINE]
4.

Advanced statistical methods for the definition of new staging models.

Kates R, Schmitt M, Harbeck N.

Recent Results Cancer Res. 2003;162:101-13. Review.

PMID:
12790325
[PubMed - indexed for MEDLINE]
5.

Artificial neural networks for prostate carcinoma risk assessment. An overview.

Montie JE, Wei JT.

Cancer. 2001 Apr 15;91(8 Suppl):1647-52. Review. No abstract available.

PMID:
11309763
[PubMed - indexed for MEDLINE]
6.

Time to stop progesterone receptor testing in breast cancer management.

Olivotto IA, Truong PT, Speers CH, Bernstein V, Allan SJ, Kelly SJ, Lesperance ML.

J Clin Oncol. 2004 May 1;22(9):1769-70. No abstract available.

PMID:
15118010
[PubMed - indexed for MEDLINE]
7.

It is not time to stop progesterone receptor testing in breast cancer.

Colomer R, Beltran M, Dorcas J, Cortes-Funes H, Hornedo J, Valentin V, Vargas C, Mendiola C, Ciruelos E.

J Clin Oncol. 2005 Jun 1;23(16):3868-9; author reply 3869-70. No abstract available.

PMID:
15923595
[PubMed - indexed for MEDLINE]
8.

A worldwide approach to the TNM staging system: collaborative efforts of the AJCC and UICC.

Greene FL, Sobin LH.

J Surg Oncol. 2009 Apr 1;99(5):269-72. doi: 10.1002/jso.21237. No abstract available.

PMID:
19170124
[PubMed - indexed for MEDLINE]
9.

Neural network analysis of clinicopathological factors in urological disease: a critical evaluation of available techniques.

Finne P, Finne R, Stenman UH.

BJU Int. 2001 Nov;88(8):825-31. No abstract available.

PMID:
11736855
[PubMed - indexed for MEDLINE]
10.

Statistical prediction models, artificial neural networks, and the sophism "I am a patient, not a statistic".

Kattan M.

J Clin Oncol. 2002 Feb 15;20(4):885-7. No abstract available.

PMID:
11844805
[PubMed - indexed for MEDLINE]
11.

Staging of non-small cell lung cancer: consensus, controversies and challenges.

van Meerbeeck JP.

Lung Cancer. 2001 Dec;34 Suppl 2:S95-107. Review.

PMID:
11720749
[PubMed - indexed for MEDLINE]
12.

Evolution and prognostic accuracy of staging system for NSCLC.

Motta G.

Lung Cancer. 2003 Dec;42 Suppl 2:S3-4. No abstract available.

PMID:
14644527
[PubMed - indexed for MEDLINE]
13.

The evolving TNM cancer staging system: an essential component of cancer care.

Brierley J; National Cancer Institute of Canada Committee on Cancer Staging.

CMAJ. 2006 Jan 17;174(2):155-6. No abstract available.

PMID:
16415456
[PubMed - indexed for MEDLINE]
Free PMC Article
14.

Artificial neural networks: a new model for assessing prognostic factors.

Grumett SA, Snow PB.

Ann Oncol. 2000 Apr;11(4):383-4. No abstract available.

PMID:
10847454
[PubMed - indexed for MEDLINE]
Free Article
15.

Outcome prediction and the future of the TNM staging system.

Burke HB.

J Natl Cancer Inst. 2004 Oct 6;96(19):1408-9. No abstract available.

PMID:
15467022
[PubMed - indexed for MEDLINE]
Free Article
16.

TNM: evolution and relation to other prognostic factors.

Sobin LH.

Semin Surg Oncol. 2003;21(1):3-7.

PMID:
12923909
[PubMed - indexed for MEDLINE]
17.

A combined neural network and decision trees model for prognosis of breast cancer relapse.

Jerez-Aragonés JM, Gómez-Ruiz JA, Ramos-Jiménez G, Muñoz-Pérez J, Alba-Conejo E.

Artif Intell Med. 2003 Jan;27(1):45-63.

PMID:
12473391
[PubMed - indexed for MEDLINE]
18.

A fuzzy logic based-method for prognostic decision making in breast and prostate cancers.

Seker H, Odetayo MO, Petrovic D, Naguib RN.

IEEE Trans Inf Technol Biomed. 2003 Jun;7(2):114-22.

PMID:
12834167
[PubMed - indexed for MEDLINE]
19.

A cancer staging perspective: the value of anatomical staging.

Greene FL.

J Surg Oncol. 2007 Jan 1;95(1):6-7. No abstract available.

PMID:
17192884
[PubMed - indexed for MEDLINE]
20.

The use of neural networks and logistic regression analysis for predicting pathological stage in men undergoing radical prostatectomy: a population based study.

Borque A, Sanz G, Allepuz C, Plaza L, Gil P, Rioja LA.

J Urol. 2001 Nov;166(5):1672-8.

PMID:
11586200
[PubMed - indexed for MEDLINE]

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